Do the media cover different groups of people differently? When they write
about minority groups, does the average tone (positive, negative, etc.) of articles change?
Do they frame similar issues in different ways depending on whether the group involved is
domestic or foreign? Do any of these patterns change over time?

Media coverage has an enormous influence on how people think about different political issues.
As such, learning about patterns and trends in this coverage is not just of general interest,
but also has considerable policy relevance. Our research on this project follows three tracks:

In the first, we investigate the tone of newspaper coverage of Muslims, (with a comparison to the coverage of Jews and Catholics).
Together with a team at Middlebury
College under the direction of professor
Erik Bleich, we collect newspaper
articles on Muslims over the past two decades from all leading newspapers. A small subset of
these are coded by hand, and this subset is used to train an automated machine coder, allowing
us to efficiently and reliably code tens of thousands of articles. This will allow us to
assess whether the tone of coverage has changed over time, and whether it differs across
newspaper types (broadsheet vs. tabloid, etc.).

Initial research has focused on British and American newspapers. Opportunities for individual research projects include looking at other minority groups (religious or otherwise) or countries.

The second track looks at the newspaper coverage of different countries and people from those countries, including refugees. Building on research
demonstrating the significance of a sense of shared identity with the people of a different
state, we collect a large corpus of newspaper articles mentioning different countries, and
develop ways of ranking the degree of shared identity implied or expressed.

The first phase draws on coverage of refugees and their countries of origin in leading U.S. and U.K. newspapers. Further research (including individual research projects) will expand the scope to a broader selection of U.S. newspapers, as well as to other countries' coverage of the United States.

The third track studies newspaper coverage of the European Union. Last summer's Brexit vote (and the acrimonious campaign that preceded it) underscored the importance of the media in driving, constraining, and shaping European integration. Even a superficial glance at the British press
makes clear how its coverage of the issue varies from that of leading papers in other EU member states.

The first phase of this project examines coverage of the European Union in the lead-up to the Brexit vote in major British papers. Once this phase has been completed, we will expand our scope to look at leading French and German papers as well.

How polarized are politics today? Are left and right further apart than they were
two or three decades ago? Is "the left" more or less to the left than it once was? Is the
U.S. left more or less to the left than the UK left?

Most scholarly research in this area has focused on Congressional speeches and votes. But
these can only tell us so much: Congressional speech is heavily focused on the legislative
issue under consideration and strongly driven by inter-party positioning.

This research project looks, instead, at political speeches aimed at general audiences.
We draw on recordings of speeches available at outlets such as Youtube. Using these, we
aim to develop a way to position speeches systematically on a left-right scale that is constant
over time and across countries.

When countries receive foreign aid, does most of it stay in the capital? Do regions affiliated
with ruling political groups receive a disproportionate share? Does food aid go to those parts of
a country where need is highest? Many questions about foreign aid require knowledge about the
targeting of aid projects within recipient states.

The AidData project, jointly run by the College of William &
Mary, Brigham Young University, and Development Gateway has made major strides in the geocoding
of aid projects using trained human coders. Examples of the results are
here
and here.
However, the sheer scope of the AidData database of projects makes it impossible to rely on manual
coding for all of it.

The state of the art in automated geocoding has improved dramatically in recent years. However,
aid data presents unique challenges: aid projects may target locations so small or obscure they
cannot be found in online databases (gazetteers); they may target multiple locations; they may
target locations whose names have changed over the years, etc.

The goal of this research project is to develop an automated geocoder whose reliability and
accuracy matches that of a trained human coders. The research has two main components:

improving the quality and quantity of data about an aid project using automated tools
for web scraping, optical character recognition, etc.

improving our ability to use contextual information ("the state of" vs. "the city of")
to identify a particular location ("New York")

For recent work using geocoding in political economy (the first one using AidData's geocoding!), see:

Why do countries give foreign aid? Thanks to the research and data collection efforts of
AidData and other scholars and organizations, we know more and
more about where aid goes, and for what types of projects. Yet the factors that determine
choices for or against particular recipient states or aid projects remain less than fully
understood.

While development agencies largely control individual project decision, national legislatures
(the U.S. Congress, the British Parliament, etc.) generally have considerable influence over
broad policy outlines. Our goal is to identify the arguments for or against aid that shape
legislative outcomes, and to uncover patterns over time and across donor states in the salience
of particular arguments. These patterns, in turn, can be used to improve our understanding of
aid policy decision-making.

We are currently systematically collecting references to foreign aid in the official legislative
records of several prominent donor countries, beginning with the United States and the United
Kingdom. Once the data collection stage has been completed, we will use machine learning
techniques to classify such references into a number of different argument categories.

What issues do international relations scholars like to study? How do they study them?
How relevant is their research to the key issues facing policymakers today? And how do
new ideas spread through the discipline and into policy, domestically and across borders?

Among others, we study patterns over time and across countries in the topics studied, theories
used and works cited by international relations scholars in different countries. In doing so, we combine information generated by human and automated coding with data about the contents of articles (frequent key words, context, etc.).

For related and similar work in political science and other disciplines, see: